Systematic analysis of self-reported comorbidities in the COSYCONET COPD cohort study by stepwise evaluation of medication

Background: In large cohort studies comorbidities are commonly self-reported by the patients. Although this is a feasible way to collect information, it only represents conditions memorized. In order to improve the use of all available information, we developed a detailed procedure to compare self-reported comorbidities with medication and applied this to the data of the German COPD cohort COSYCONET. Methods: Approach I was based solely on ICD-10-codes for the diseases and the indications of medications. To deal with the non-specificity of medications, Approach II focused on disease-specific medication and ATC-codes. The relationship between comorbidities and medication was expressed by a four-level concordance score. Results: Approach I and II demonstrated that the patterns of concordance scores markedly differed between diseases. On average, Approach I resulted in more than 50% concordance of all reported diseases to at least one medication. Approach II showed particularly large differences in its ability of matching with medications, due to large differences in the disease-specificity of drugs, e.g. for diabetes versus specific cardiovascular disorders. Conclusion: Both approaches provide defined strategies to confirm self-reported diagnoses via medication. Approach I covers a broad spectrum of diseases and medications but is limited regarding disease-specific information. Approach II is based on medications specific for a disease and can reach higher concordance. The strategies described are generally applicable in large studies to extract as much information as possible from the available data. Funded by BMBF COSYCONET and Mundipharma GmbH .